AN INTELLIGENT DECISION SUPPORT TOOL FOR EARLY DIAGNOSIS OF FUNCTIONAL PITUITARY ADENOMAS

Gokbay I. Z., KARAMAN S. L., Yarman S., Yarman B. S.

TWMS JOURNAL OF APPLIED AND ENGINEERING MATHEMATICS, cilt.5, sa.2, ss.169-187, 2015 (ESCI) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 5 Sayı: 2
  • Basım Tarihi: 2015
  • Dergi Adı: TWMS JOURNAL OF APPLIED AND ENGINEERING MATHEMATICS
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), TR DİZİN (ULAKBİM)
  • Sayfa Sayıları: ss.169-187
  • İstanbul Üniversitesi Adresli: Evet

Özet

In this work, a web based integrated Medical Decision Support System (MDSS) tool for mainly early diagnosis of functional pituitary adenomas (i.e., somatotrophinoma, corticotrophinoma and prolactinoma) is developed. In the MDSS tool, hormone diseases are described by means of well-classified set of attributes generated from the typical sign and symptoms of disorders.The proposed tool is based on a stationary linear stochastic system model which specifically predicts the selected hormone diseases employing certain system parameters. The MDSS tool is user friendly which includes questions and answers at the opening session of the self-test. Questions and answers session will be completed by "yes" or "no" type of simple-responses. Based on our clinical results, MDSS tool yields more than 99% correct decisions on the selected hormone diseases. It is expected that effective use of the proposed MDSS tool will save substantial amount of valuable time of an expert endocrinologists and minimizes the cost of diagnosis. Furthermore, it will provide the opportunity for early diagnosis for the patient and the expert medical doctor to take the necessary preventive measures.